Technical Field
The present invention relates to battery degradation and, in particular, to measuring and predicting battery degradation.
Description of the Related Art
As rechargeable batteries become integrated more deeply in every-day operations, including mobile computing devices, electric vehicles, smart grids, and the like, improved analysis of the performance of such batteries becomes a pressing concern. In particular, battery life is degraded through use. Predicting and controlling capacity retention rate (i.e., battery life) from usage history is particularly important, as the capacity retention rate is directly related to the remaining usable time of the vehicle or device.
Existing models for predicting capacity retention rate include the square root law model. In this model, capacity retention rate is degraded proportional to the square root of the cumulative use time due to formation of a solid-electrolyte interphase (SEI) layer on the anode of the battery. This applies particularly to lithium-based batteries, as the SEI layer reduces the lithium ion irreversibly, and its accumulation is proportional to the square root of the cumulative use time. Thus, following the square root law model, the capacity retention rate is modeled as y=−atb+c, where t is the cumulative use time, b is generally ½, and a and c are parameters that depend on the particular battery.
However, in many real-world applications, battery degradation is not simply proportional to the square root of the cumulative use time. As a result, the square root law model is not adequate for high-precision analysis of batteries' capacity retention rates.